Run predictions from the results of pmcmc(). This
function can also be called by running predict() on
the object, using R's S3 dispatch.
pmcmc_predict(
object,
times,
prepend_trajectories = FALSE,
n_threads = NULL,
seed = NULL
)The results of running pmcmc() with
return_state = TRUE (without this extra information,
prediction is not possible)
A vector of time times to return predictions for. The
first value must be the final value run in your simulation. An
error will be thrown if you get this value wrong, look in
object$predict$time (or the error message) for the
correct value.
Prepend trajectories from the particle filter to the predictions created here.
The number of threads used in the simulation. If not given, we default to the value used in the particle filter that was used in the pmcmc.
The random number seed (see particle_filter). The
default value of NULL will seed the dust random number
generator from R's random number generator. However, you can
pick up from the same RNG stream used in the simulation if you
pass in seed = object$predict$seed. However, do not do this if
you are gong to run pmcmc_predict() multiple times the result
will be identical. If you do want to call predict with this
state multiple times you should create a persistant rng state
object (e.g., with dust::dust_rng and perform a "long jump"
between each call.